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09/18/2023
Empirical Study of Mix-based Data Augmentation Methods in Physiological Time Series Data
Data augmentation is a common practice to help generalization in the pro...
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03/16/2023
Towards the Understanding of Receptivity and Affect in EMAs using Physiological based Machine Learning Method: Analysis of Receptivity and Affect
As mobile health (mHealth) studies become increasingly productive due to...
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11/21/2022
PiRL: Participant-Invariant Representation Learning for Healthcare
Due to individual heterogeneity, performance gaps are observed between g...
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10/13/2022
LEAVES: Learning Views for Time-Series Data in Contrastive Learning
Contrastive learning, a self-supervised learning method that can learn r...
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10/13/2022
Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep Learning
Deep learning has performed remarkably well on many tasks recently. Howe...
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08/07/2022
Bias Reducing Multitask Learning on Mental Health Prediction
There has been an increase in research in developing machine learning mo...
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07/12/2022
Exploiting Social Graph Networks for Emotion Prediction
Emotion prediction plays an essential role in mental health and emotion-...
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05/24/2022
Psychotic Relapse Prediction in Schizophrenia Patients using A Mobile Sensing-based Supervised Deep Learning Model
Mobile sensing-based modeling of behavioral changes could predict an onc...
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02/22/2022
Semi-Supervised Learning and Data Augmentation in Wearable-based Momentary Stress Detection in the Wild
Physiological and behavioral data collected from wearable or mobile sens...
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02/16/2022
More to Less (M2L): Enhanced Health Recognition in the Wild with Reduced Modality of Wearable Sensors
Accurately recognizing health-related conditions from wearable data is c...
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07/19/2021
Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the Wild
Multimodal wearable physiological data in daily life have been used to e...
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06/22/2021
Forecasting Health and Wellbeing for Shift Workers Using Job-role Based Deep Neural Network
Shift workers who are essential contributors to our society, face high r...
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06/22/2021
Routine Clustering of Mobile Sensor Data Facilitates Psychotic Relapse Prediction in Schizophrenia Patients
We aim to develop clustering models to obtain behavioral representations...
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08/20/2019